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International Journal of Thermofluids 2025年 27卷

作者： Okasha, Mostafa Mohamed Abbas, Munawar Ghaeb, Fadhil A. Shernazarov, Iskandar Younis, Jihad Tharwan, Mohammed Agha, Afnan Al Garalleh, Hakim AL Department of Mechanical Engineering College of Engineering Northern Border University Arar Saudi Arabia Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai602105 India Department of Mathematics The Islamia University of Bahawalpur Bahawalpur63100 Pakistan Petroleum and Mining Engineering Department Tishk International University Erbil Iraq Department of Chemistry and Its Teaching Methods Tashkent State Pedagogical University Tashkent Uzbekistan Department of Mathematics Aden University P.O.Box 6014 Aden Yemen Department of Mechanical Engineering College of Engineering and Computer Sciences Jazan University P. O. Box 45142 Jazan Saudi Arabia Department of Mathematical Science College of Engineering University of Business and Technology Jeddah21361 Saudi Arabia

Background: Examining the effects of elastic deformation and melting phenomena on mass and heat transmission while examining the constant two-dimensional flow of a dusty hybrid nanofluid over a sheet containing gyrotactic microbes and porous media is the primary objective of this investigation. Method: The controlling partial differential equations are converted into ordinary differential equations by using the proper similarity transformation. The system of equations is then numerically solved using an efficient bvp4c approach. Applications: In the realm of bioengineering, this model is very useful, especially when constructing sophisticated cooling systems for biomedical devices where accurate temperature control is essential. The model's insights are also useful in environmental engineering, where they can be used to improve pollutant removal methods in water treatment procedures by enhancing bioconvective flows. This research also offers greater control over manufacturing operations that need precise temperature and fluid dynamic management in industrial processes involving the manipulation of non-Newtonian fluids. Outcomes: As the elastic deformation increases, the concentration and temperature distributions decrease. The velocity, microorganism's, thermal and concentration field enhance as augments the value of melting parameter. © 2025

关键词： Non Newtonian flow

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Capacity limit of deep learning methods on scenarios of pigs in farrowing pen under occlusion

Capacity limit of deep learning methods on scenarios of pigs...

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2021 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2021

作者： Huang, Endai Mao, Axiu Ceballos, Maria Camila Parsons, Thomas D. Liu, Kai Department of Computer Science City University of Hong Kong Hong Kong Department of Infectious Diseases and Public Health City University of Hong Kong Hong Kong Department of Production Animal Health Faculty of Veterinary Medicine University of Calgary CalgaryAB Canada Swine Teaching and Research Center School of Veterinary Medicine University of Pennsylvania Kennett SquarePA United States

ISBN: (纸本)9781713833536

Deep learning has achieved great success in computer vision. However, most of the existing methods are designed and tested on public datasets without severe occlusions, which may lead to low recall or even algorithm failure in real-world animal industry where occlusions commonly exist. Therefore, whether deep learning methods are still applicable in scenes with frequently occurring occlusions remains to be verified. This study assessed the applicability and capacity limit of deep learning methods on scenarios of pigs in farrowing pens as a case study. We collected 1,100 images from a farrowing pen where farrowing crate was adopted, and 94.8% of images have at least one piglet under occlusion. Six state-of-the-art deep learning methods in three major computer vision tasks, including object detection (Faster RCNN and Yolov4), semantic segmentation (FCN and Unet), and instance segmentation (Mask RCNN and Yolact++) were evaluated, respectively. To further challenge these methods, we randomly and gradually added virtual occlusions in ten cases on the images and tested their capacity limitation under extreme occlusion. The result showed that all the six deep learning methods achieved satisfactory performance on the original baseline case while the performance fell when occlusion became heavier. Object detection methods were less affected by occlusion than instance segmentation methods due to their rougher output. Semantic segmentation method Unet demonstrated the least effect by occlusion due to its pixel-wise classification characters, while the instance segmentation method Mask RCNN was most affected by occlusion. We suggest further study on segmentation method in animal industry. © ASABE 2021 Annual International Meeting

关键词： Object detection

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Event-based Pathology Data Prioritisation: A Study using Multi-variate Time Series Classification 13

Event-based Pathology Data Prioritisation: A Study using Mul...

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13th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2021 as part of 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2021

作者： Qi, Jing Burnside, Girvan Charnley, Paul Coenen, Frans Department of Computer Science University of Liverpool LiverpoolL69 3BX United Kingdom Department of Biostatistics University of Liverpool LiverpoolL69 3BX United Kingdom Wirral University Teaching Hospital NHS Foundation Trust Arrowe Park Hospital Wirral CH49 5PE United Kingdom

ISBN: (纸本)9789897585333

A particular challenge for any hospital is the large amount of pathology data that doctors are routinely presented with. Pathology result analysis is routine in hospital environments. Some form of machine learning for pathology result prioritisation is therefore desirable. Patients typically have a history of pathology results, and each pathology result may have several dimensions, hence time series analysis for prioritisation suggests itself. However, because of the resource required, labelled prioritisation training data is typically not readily available. Hence traditional supervised learning and/or ranking is not a realistic solution and some alternative solution is required. The idea presented in this paper is to use the outcome event, what happened to a patient, as a proxy for a ground truth prioritisation data set. This idea is explored using two approaches: kNN time series classification and Long Short-Term Memory deep learning. Copyright © 2021 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved.

关键词： Long short-term memory

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“Research and Practice of Students”Academic Achievement Evaluation Based on “Web Design” Course

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Journal of Contemporary Educational Research 2020年第9期4卷 79-83页

作者： Yunting Bao Huijuan Zhang School of Computer Science Southwest Petroleum UniversityChengdu CitySichuan ProvinceChina Computer Engineering Teaching and Research Office Beijing Automation Engineering SchoolBeijingChina

In view of the drawbacks of students’academic achievement evaluation in the traditional“Web Design”course,this paper applies the theory of diversity and development to the evaluation of students’academic achievement in the course of“Web Design”,improving the traditional way in the evaluation concept,subject,mode and content,and initially constructing the evaluation scheme for students’academic achievement of“Web Design”course,which improves students’interest in learning and promotes students’development and professional development.

关键词： Multiple Development Evaluation

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Research on Differentially Private Bayesian Classification Algorithm for Data Streams 4

Research on Differentially Private Bayesian Classification A...

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4th IEEE International Conference on Big Data Analytics, ICBDA 2019

作者： Zhang, Guozheng Li, Shuyu School of Computer Science Shaanxi Normal University Xi'an China Key Laboratory of Modern Teaching Technology Ministry of Education School of Computer Science Shaanxi Normal University Xi'an China

ISBN: (纸本)9781728112824

Considering the privacy leakage risk of data streams mining, a differential private Naive Bayes classification algorithm for data streams (DP-NB) is proposed in the paper. The Gaussian Bayesian model is firstly adopted and the methods of feature selection, cross-validation and weighting mechanism are used to improve the model and solve the problem of concept drift. Then noise perturbation is added to the model parameters and incremental update is presented to optimize the Gaussian classifier model. Theoretical analysis of the DP-NB algorithm proves that it achieves \mathcal{E}- differential privacy. Finally, experimental results show that the DP-NB algorithm has better classification accuracy while satisfying privacy protection. © 2019 IEEE.

关键词： Data privacy

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VideoCutTool - Online Video Editor Tool for Wikimedia Commons

VideoCutTool - Online Video Editor Tool for Wikimedia Common...

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International Conference on Communications and Signal Processing

作者： Gopa Vasanth James Heilman Pratik Shetty Hassan Amin M Geetha Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amritapuri India Department of Emergency Medicine Cranbrook Canada founder of VideoWiki Mumbai India teaching assistance of Computer Science Faculty of Science Helwan University Egypt

ISBN: (数字)9781728149882

ISBN: (纸本)9781728149899

The image CropTool allows users to crop images present on Wikimedia Commons without leaving the Wikimedia family of sites within a web environment. We implemented the same workflow for videos with the VideoCutTool. Previously, a video on Wikimedia Commons had to be downloaded, changed, and later re-uploaded to Commons. The previous process took a significant amount of time and requires the use of outside software, while the VideoCutTool allows authorized users to work up-to 10x faster. This paper talks about the features of VideoCutTool and its implementation. The tool is currently live on https://***/video-cut-tool/ and published under the Creative Commons Attribution-ShareAlike 4.0 licence.

关键词： Tools Agriculture Encoding Uniform resource locators Watermarking Electronic mail Information services

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Using computer-generated concept maps in the engineering design process to improve physics learning

Using computer-generated concept maps in the engineering des...

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2020 ASEE Virtual Annual Conference, ASEE 2020

作者： Rugh, Michael S. Beyette, Donald Joseph Capraro, Mary Margaret Capraro, Robert M. Aggie STEM Texas A&M University United States Department of Computer Science and Engineering Texas A&M University United States Department of Teaching Learning and Culture Texas A&M University United States

Students engage in the Engineering Design Process and explore the relationships between concepts involved in simple rotational motion using automatically generated Dynamic and Interactive Mathematical Expressions (DIME) maps. Provided with DIME maps while researching and exploring concepts, students can visualize the connections between concepts and better understand how the physics concepts affects the design of their spinning objects. © American Society for Engineering Education 2020.

关键词： Design

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AR-Classroom: Integrating Conversational Artificial Intelligence with Augmented Reality Technology for Learning Spatial Transformations and Their Matrix Representation

AR-Classroom: Integrating Conversational Artificial Intellig...

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Frontiers in Education (FIE) Conference

作者： Uttamasha Monjoree Samantha D. Aguilar Chengyuan Qian Carl Van Huyck Shu-Hao Yeh Preston Tranbarger Luke Duane-Tessier Leo Solitare-Renaldo Heather Burte Philip Yasskin Jeffrey Liew Dezhen Song Francis Quek Wei Yan Dept. Architecture Texas A&M University College Station USA Dept. Educational Psychology Texas A&M University College Station USA Dept. Computer Sci. & Eng. Texas A&M University College Station USA Dept. Visualization Texas A&M University College Station USA Dept. Mathematics Texas A&M University College Station USA Haverford College Haverford USA Dept. Computer Science Carnegie Mellon University Pittsburgh USA Dept. Teaching Learning & Culture Texas A&M University College Station USA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This research full paper describes the AR-Classroom application that utilizes augmented reality (AR) and physical and virtual manipulatives to enable undergraduate students to build intuition about the relation between spatial transformations and their mathematical representations. To further build on the app's usability and functionality, additional features are being prototyped to continue improving the user-app interaction with the AR-Classroom. Some of the challenges the students faced when using AR-Classroom were recalling basic matrix operations without geometric context, basic trigonometric functions and their applications in the two-dimensional space, loss of AR registration for not understanding the AR environment, and User Interface (UI) issues. To address these issues, a conversational Artificial Intelligence (AI)-based multi-sensory and interactive assistance has been added to the AR-Classroom. Integrating sophisticated language processing and response generation of AI with immersive three-dimensional capabilities of AR can create a more engaging learning experience than the previous versions of the app. This integration focuses on creating a symbiosis between AR and AI. It creates an elevated user experience by offering real-time, personalized assistance to students dealing with issues related to understanding mathematical concepts and functionalities of the app. A qualitative exploratory usability study was done to assess the user's interaction with the AI implemented in the AR-Classroom, aiming to explore the AI's ability to guide students in using AR technology and aid in introductory matrix algebra learning, to effectively serve the students' learning. Based on the thematic analysis of the user experiment we found four main themes related to users' perceptions of AR-Classroom AI features usability: (1) AI chatbot ease-of-use, (2) Need for answer elaboration from AI, (3) Desire for visual information, and (4) Increased understanding of the content ar

关键词： Symbiosis Visualization Learning (artificial intelligence) User interfaces Matrices User experience Real-time systems Artificial intelligence Usability Augmented reality

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Application of fractional derivatives in modeling the heat flow in the thermal protection system

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Communications in Nonlinear science and Numerical Simulation 2025年 150卷

作者： Rafał Brociek Edyta Hetmaniok Damian Słota Department of Artificial Intelligence Modelling Silesian University of Technology Kaszubska 23 Gliwice 44-100 Poland Department of Mathematical Methods in Technology and Computer Science Silesian University of Technology Kaszubska 23 Gliwice 44-100 Poland

This work focuses on the development of a mathematical model of the thermal protection system, in which the fractional Caputo derivative is used for the first time in one of the layers of the model. So far, no studies have been identified that consider a model of this kind. The introduction of fractional derivatives is justified by the porous structure of the considered layer because in this type of media the description of heat flow using the fractional derivatives generally better reconstructs the real processes compared to the classical approach. The boundary condition of the second kind is set on the external surface, taking into account the aerothermal heat flux and the re-radiation heat flux. Whereas, on the internal surface, the boundary condition of the first kind is applied. The model also includes the nonzero thermal resistances between layers and the dependence on temperature of the material parameters. In this paper, the numerical solutions of direct problem obtained by using the finite difference method are analyzed. The calculations were performed for various grids, which confirmed the convergence of the results along with the mesh getting denser. Moreover, calculations were also made for various values of the order of the Caputo derivative. The results showed that when the order of the Caputo derivative tends to one, the obtained solution converges to the solution of the model with only classical derivatives. Additionally, an application of technique based on the ”short memory principle” is tested, which allows us to significantly reduce the computation time.

关键词： Thermal protection system Aerothermal heat flux Mathematical modeling Caputo fractional derivative

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A Consensus Privacy Metrics Framework for Synthetic Data

arXiv

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arXiv 2025年

作者： Pilgram, Lisa Dankar, Fida K. Drechsler, Jörg Elliot, Mark Domingo-Ferrer, Josep Francis, Paul Kantarcioglu, Murat Kong, Linglong Malin, Bradley Muralidhar, Krishnamurty Myles, Puja Prasser, Fabian Raisaro, Jean Louis Yan, Chao El Emam, Khaled School of Epidemiology and Public Health University of Ottawa ON Canada CHEO Research Institute ON Canada Department of Nephrology and Medical Intensive Care Charité – Universitätsmedizin Berlin Berlin Germany Department for Statistical Methods Institute for Employment Research Nuernberg Germany Institute for Statistics Ludwig-Maximilians-Universität Munich Germany Joint Program in Survey Methodology University of Maryland United States The Cathie Marsh Institute Research School of Social Sciences University of Manchester Manchester United Kingdom Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Catalonia Tarragona Spain Max Planck Institute for Software Systems Germany Department of Computer Science Virginia Tech United States Department of Mathematical and Statistical Sciences University of Alberta Alberta Canada Department of Biomedical Informatics Vanderbilt University Medical Center NashvilleTN United States Department of Biostatistics Vanderbilt University Medical Center NashvilleTN United States Department of Computer Science Vanderbilt University NashvilleTN United States Department of Marketing and Supply Chain Management University of Oklahoma Oklahoma United States Medicines and Healthcare products Regulatory Agency London United Kingdom Berlin Institute of Health at Charité Universitätsmedizin Berlin Medical Informatics Group Berlin Germany Biomedical Data Science Center University Hospital Lausanne Lausanne Switzerland

Synthetic data generation is one approach for sharing individual-level data. However, to meet legislative requirements, it is necessary to demonstrate that the individuals’ privacy is adequately protected. There is no consolidated standard for measuring privacy in synthetic data. Through an expert panel and consensus process, we developed a framework for evaluating privacy in synthetic data. Our findings indicate that current similarity metrics fail to measure identity disclosure, and their use is discouraged. For differentially private synthetic data, a privacy budget other than close to zero was not considered interpretable. There was consensus on the importance of membership and attribute disclosure, both of which involve inferring personal information about an individual without necessarily revealing their identity. The resultant framework provides precise recommendations for metrics that address these types of disclosures effectively. Our findings further present specific opportunities for future research that can help with widespread adoption of synthetic data. © 2025, CC BY.

关键词： Differential privacy

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